Evidence map›Paper›PMID 27690208›Full record

ArticleBioengineered2017

Genomic feature extraction and comparison based on global alignment of ChIP-sequencing data.

Binhua Tang

Abstract read
In one paragraph

Article in Bioengineered, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Binhua Tanga Epigenetics & Function Group , College of the Internet of Things, Hohai University , Jiangsu , China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Enhanced accuracy and high-throughput capability in capturing genetic activities lead ChIP-sequencing technology to be applied prevalently in diverse study for tackling DNA-protein interaction problems. Till now, such questions as deciding suitable ChIP-seq arguments and comparing sample quality still haunt biologists. We propose the methods for answering such questions as deciding optimal argument pairs in global alignment of ChIP sequencing data; then we employ a modern signal processing approach to extract inherent genomic features from the global alignments of transcriptional binding activities; together with pairwise comparison from intra- and inter-sample perspectives; thus we can further determine alignment quality and decide the optimal candidate for multi-source heterogeneous high-throughput sequences. The work provides a practical approach to quantitatively compare the alignment quality for heterogeneous sequencing data, especially in determining the efficiency of transcriptional binding from replicate samples, thus it helps to exploit the potentiality of ChIP-seq for deep comprehension of inherent biological meanings from the high-throughput genomic sequences.

Indexed as

AlgorithmsChromatin ImmunoprecipitationChromosome MappingDNADNA-Binding ProteinsHigh-Throughput Nucleotide SequencingSequence AlignmentSequence Analysis, DNADNADNA-Binding ProteinsChIP-seqcomprehensive analysisgenomic featureoptimal argument

Identifiers

PMID27690208
PMCPMC5470523

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.